The latest Morgan Stanley survey reveals a striking shift in how the next generation of finance professionals approaches both technology and risk-taking. Summer interns, often seen glued to their smartphones during breaks, are increasingly splitting their attention between algorithmic trading simulations and decentralized prediction platforms. This behavior reflects a broader cultural move where young adults treat forecasting not just as a theoretical exercise but as a tangible, accessible tool for understanding market sentiment. The data suggests that these interns are not merely experimenting; they are integrating these platforms into their daily information diet, blending traditional financial analysis with crowdsourced insights. For firms, this trend signals a need to reassess how entry‑level talent is trained and monitored, especially as the lines between casual speculation and professional analysis become blurrier.
Conducted over the summer and released in August, the study gathered responses from more than five hundred interns across North America, the majority of whom are twenty‑one years old or younger. This demographic snapshot offers a rare glimpse into the habits of individuals who are about to enter full‑time roles at major banks, hedge funds, and asset managers. The survey’s timing—coinciding with the peak of internship season—captures behaviors that are likely to persist as these young professionals transition into analysts and associates. Notably, this was the first time Morgan Stanley explicitly asked about prediction‑market usage alongside AI adoption, highlighting the firm’s recognition of parallel technological disruptions shaping the industry’s future talent pool.
Approximately twenty‑eight percent of respondents reported having used a betting or prediction‑market app within the past twelve months, with Kalshi and Polymarket emerging as the clear frontrunners. Among those who engaged with these platforms, roughly fourteen percent cited Kalshi as their primary choice, while a majority—fifty‑five percent—indicated they maintain accounts on multiple services simultaneously. This multi‑platform approach suggests interns are not merely dabbling; they are actively comparing odds, seeking arbitrage opportunities, and treating prediction markets as a supplemental research tool. Such behavior mirrors the way professional traders use various data feeds to triangulate market expectations, hinting at an early‑stage adoption of sophisticated information‑gathering habits.
When placed beside broader population metrics, the interns’ engagement levels appear remarkably aligned with national trends. A separate Harris Poll survey conducted in May found that twenty‑one percent of U.S. adults had tried a prediction‑market platform, a figure that closely mirrors the intern cohort. Interestingly, the same poll showed that thirty‑seven percent of respondents aged eighteen to thirty‑four reported usage, indicating that the intern group sits slightly below the peak for their age bracket but still represents a significant penetration. This alignment suggests that the allure of prediction markets is less a generational quirk and more a reflection of wider societal curiosity about probabilistic forecasting in an era of heightened uncertainty.
The rising popularity of these apps has not gone unnoticed by regulators and compliance officers. Several states have launched investigations or issued cease‑and‑desist letters against operators accused of offering unlicensed gambling products, while a growing number of employers have amended internal policies to prohibit trading on such platforms during work hours. A source familiar with Morgan Stanley’s internal guidelines confirmed that the firm’s code of conduct already encompasses prediction markets under its broader trading and investing provisions, though specifics were not disclosed. This regulatory backdrop creates a tension: interns are drawn to the platforms’ real‑time sentiment signals, yet firms must balance the desire for innovative data sources against potential legal and reputational risks.
Kalshi’s institutional outreach efforts provide further context for the platform’s appeal among young finance professionals. In prior interviews, the company’s head of institutional sales described a deliberate strategy to attract Wall Street firms by positioning Kalshi not just as a betting venue but as a source of alternative data that can complement traditional fundamentals and technical analysis. The pitch emphasizes the platform’s ability to aggregate public expectations on macroeconomic events, earnings outcomes, and geopolitical developments—information that can serve as a leading indicator for price movements. Nonetheless, skeptics warn that the limited oversight and potential for insider information leakage could undermine market integrity, a concern that resonates strongly with compliance‑focused institutions.
Artificial intelligence usage among the intern cohort has experienced explosive growth, with sixty‑eight percent stating they rely on an AI tool on a daily basis—a figure that has more than doubled since the previous year and risen nearly fivefold compared to 2024 levels. This surge underscores how rapidly generative AI has permeated everyday workflows, transforming tasks that once required hours of manual effort into near‑instantaneous outputs. For many interns, AI has become a ubiquitous study aid, a drafting assistant, and a quick‑reference consultant, effectively reshaping the skill set expected of entry‑level finance professionals.
Beyond casual use, a substantial seventy percent of interns now personally subscribe to premium versions of AI services, up from fifty‑two percent the prior summer. Their primary applications include learning unfamiliar concepts, polishing written communications, and condensing lengthy reports into digestible summaries. Notably, they express particular comfort delegating research‑oriented tasks to AI agents—such as scanning news feeds for relevant headlines or comparing pricing data across securities—suggesting a trust in the technology’s ability to handle repetitive, information‑intensive chores. This shift allows interns to allocate more cognitive bandwidth toward higher‑order analysis and strategic thinking.
Despite the enthusiasm, a palpable undercurrent of anxiety runs through the cohort regarding AI’s impact on employment. Sixty‑one percent of respondents admitted they are at least somewhat concerned that AI could displace traditional finance roles, a sentiment that intensifies when looking beyond the industry—where seventy‑four percent fear job losses in other sectors. These worries are not unfounded; historical precedents show that automation often reshapes rather than eliminates work, but the pace and scale of current AI advancements raise legitimate questions about the future demand for analysts, associates, and even junior traders. The tension between embracing efficiency and safeguarding livelihoods defines a central dilemma for the next generation of Wall Street talent.
Interest in embodied AI, particularly humanoid robots, also features prominently in the interns’ outlook. Physical AI startups—companies building robots capable of interacting with the physical world—secured a staggering $16.3 billion in funding during the first quarter of the year alone, according to PitchBook data, underscoring investor confidence in the sector’s long‑term potential. More than sixty percent of interns said they would at least consider having a humanoid robot at home, with ten percent labeling themselves as likely early adopters. The survey authors noted that this enthusiasm could foreshadow a rapid expansion of consumer‑grade robotics, signaling that the interns’ tech optimism extends beyond software into tangible, everyday applications.
Written responses to the survey revealed a deeper layer of Gen Z‑specific anxieties, especially concerning the intersection of AI, academic pressure, and economic outlook. Several interns lamented that college has devolved into a relentless scramble to secure prestigious internships, leaving little room for self‑exploration or intellectual curiosity. Others described an overwhelming flood of low‑quality AI‑generated content—referred to colloquially as an “AI slop overdose”—that complicates genuine learning. A recurring theme was the perception of incessant competition, not just for jobs but for validation, creating an environment where achievement feels perpetually provisional.
One particularly poignant comment captured the generational tension: interns acknowledged that while their aspirations may differ in form from those of older cohorts, the underlying desire for stability—steady careers, homeownership, family life—remains strong. Yet they expressed frustration that macroeconomic forces, housing costs, and market volatility make those traditional milestones feel increasingly out of reach. This sentiment highlights a broader disillusionment with the promise of meritocracy, suggesting that financial firms may need to address not only skill development but also the existential concerns of their youngest employees to foster long‑term engagement and loyalty.
For interns navigating this complex landscape, the key is to harness emerging tools judiciously while cultivating a resilient, adaptable mindset. Treat prediction markets as a supplementary data source—one that offers sentiment snapshots but should never replace rigorous fundamental analysis or risk management frameworks. Maintain strict adherence to your firm’s compliance policies; if unsure about the permissibility of a platform, seek guidance before engaging. Leverage AI to automate routine tasks, but invest the saved time in developing critical thinking, domain expertise, and ethical judgment—skills that algorithms cannot replicate. Stay informed about regulatory developments surrounding both AI and alternative data platforms, as ignorance could expose you to unintended violations. Finally, balance technological optimism with realistic career planning: diversify your skill set, seek mentorship, and remain proactive about lifelong learning to thrive amid the inevitable shifts reshaping Wall Street.